Netherlands

Moral inference is an emerging topic of critical importance in artificial intelligence. The contemporary approach often relies on language modelling to infer moral relevance or moral properties of a concept such as &quot;smoking&quot;. This approach  demands complex parameterisation and costly computation, and it tends to disconnect with psychological accounts of moralization. We present a simple cognitive model for moral inference grounded in theories of moralization. Our model  builds on word association network known to  capture  human semantics and draws on rich psychological data. We demonstrate that our moral association graph model performs competitively to state-of-the-art language models, where we evaluate them against a comprehensive set of data for  automated inference of moral norms and moral judgment of concepts, and in-context moral inference. Moreover, we show that our model discovers intuitive concepts underlying  moral judgment and is applicable to informing short-term temporal changes in moral perception.

**Authors:**

Aida Ramezani: University of Toronto; Yang Xu: University of Toronto

CogSci 2024

Moral association graph: A cognitive model for moral inference

### Welcome to CogSci Conference 2025!

The 47th Annual Meeting of the Cognitive Science Society was a hybrid meeting held in San Francisco. 

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#### About

The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education.

The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

#### Our History 

* **Society Creation**<br>
The Society was incorporated as a 501(c)(3) non-profit professional organization in Massachusetts in 1979. The organizing committee included Roger Schank, Allan Collins, Donald Norman, and a number of other scholars from psychology, linguistics, computer science, and philosophy. 
<br><br>
* **Conference Creation**<br>
The first conference on cognitive science was held at La Jolla, California in August, 1979, and has occurred annually since then. The proceedings of each conference are published, and those from most years are available through Lawrence Erlbaum Associates, Inc. The annual proceedings of the Cognitive Science Conference represent a major source of information on new work and new ideas in the scientific study of thinking. In 1990, the Society, with help from an anonymous donor, established the David Marr Prize for the best student paper at each annual meeting.
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* **Journal Creation**<br>
The Journal, Cognitive Science, began publication in 1976, and is now published by Wiley-Blackwell. The Executive Editor is currently Richard P. Cooper of Birkbeck, University of London, and there are 18 Associate Editors and a 30-member editorial board. It serves as the premier outlet for research reports that intersect two or more disciplines. Copyrights for articles published in the journal are held by the Society. The Governing Board of the Cognitive Science Society voted in late 2006 to found a new journal, Topics in Cognitive Science (topiCS). The Editor in Chief is Wayne Gray, Cognitive Science Department, Rensselaer Polytechnic Institute. The journal seeks to fill a niche not occupied by Cognitive Science Journal or other cognitive science journals. Membership in the Society includes a subscription to Cognitive Science and TopiCS. Copyrights for articles published in the journal are held by the Society.
<br><br>

#### Code of Conduct

By attending the CogSci 2025 Conference, you are required to adhere to the society’s **[Code of Conduct](https://drive.google.com/file/d/1ChPuihLy6jE_BWqfO7J2KKgX35JW2zsM/view?usp=sharing)**.
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CogSci 2025

The 47th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

Moral inference is an emerging topic of critical importance in artificial intelligence. The contemporary approach often relies on language modelling to infer moral relevance or moral properties of a concept such as "smoking". This approach  demands complex parameterisation and costly computation, and it tends to disconnect with psychological accounts of moralization. We present a simple cognitive model for moral inference grounded in theories of moralization. Our model  builds on word association network known to  capture  human semantics and draws on rich psychological data. We demonstrate that our moral association graph model performs competitively to state-of-the-art language models, where we evaluate them against a comprehensive set of data for  automated inference of moral norms and moral judgment of concepts, and in-context moral inference. Moreover, we show that our model discovers intuitive concepts underlying  moral judgment and is applicable to informing short-term temporal changes in moral perception.

**Authors:**

Aida Ramezani: University of Toronto; Yang Xu: University of Toronto

technical paper

The 46th Annual Meeting of the Cognitive Science Society was an in-person meeting held in Rotterdam, The Netherlands at the Postillion Hotel & Conference Centre.

**ON-DEMAND PROGRAM ACCESS AFTER THE CONFERENCE**<br>
Recordings of the invited program are now available. You can access them by clicking on the 'Schedule' icon on the left. Select view by week and navigate to the day and time slot of the recording you wish to view. Click on the time slot to access the recording.

Recordings available (click on each recording to view):

**Thursday, July 25**<br>
0900: [Keynote Speaker Morgan Barense on Enhancing real-world event memory](https://underline.io/events/465/sessions/17997/lecture/99084-dynamics-between-minds-and-the-environment)<br>
1000: [Gleitman Award Winner Isabelle Dautriche on Language Foundations: Insights from acquisition, communication, cognition, and more](https://underline.io/events/465/sessions/18000/lecture/99085-gleitman-talk)<br>
1415: [Invited Symposium: Dynamics between minds and the environment](https://underline.io/events/465/sessions?eventSessionId=18016&searchGroup=lecture)<br>
1700: [Rumelhart Prize Presentation Speaker Alison Gopnik on Exploit, explore, empower: Three ages and three intelligences](https://underline.io/events/465/sessions/18028/lecture/99161-rp1-rumelhart-prize-presentation)<br>

**Friday, July 26**<br>
0900: [C.L. de Carvalho-Heineken Prize Keynote Speaker Kia Nobre on Focusing in memory](https://underline.io/events/465/sessions/18035/lecture/99162-hp1-c-l-de-carvalho-heineken-prize-keynote-address)<br>
1030: [Rumelhart Symposium: Childhood as exploration](https://underline.io/events/465/sessions/18038/lecture/100346-childhood-as-exploration)<br>
1415: [Elman Prize Symposium](https://underline.io/events/465/sessions?eventSessionId=18053&searchGroup=lecture)<br>
1600: [Invited Symposium: Dynamics between minds](https://underline.io/events/465/sessions?eventSessionId=18065&searchGroup=lecture)<br>
1745: [Keynote Speaker Andrea E. Martin on Neural dynamics encode the structure and statistics of language](https://underline.io/events/465/sessions/18077/lecture/99271-neural-dynamics-encode-the-structure-and-statistics-of-language)<br>

**Saturday, July 27**<br>
0900: [Keynote Speaker Gregor Schöner on How higher cognition emerges from the dynamics of strongly interacting neural populations](https://underline.io/events/465/sessions/18083/lecture/99273-dynamics-within-the-mind)<br>
1000: [Glushko Talks](https://underline.io/events/465/sessions?eventSessionId=18086&searchGroup=lecture)<br>
1500: [Invited Symposium: Dynamics within minds](https://underline.io/events/465/sessions?eventSessionId=18100&searchGroup=lecture)<br>


#### **CogSci 2024 Program Book**
<div style="position:relative;padding-top:0;width:900px;height:500px;"><iframe style="position:absolute;border:none;width:100%;height:100%;left:0;top:0;" src="https://online.fliphtml5.com/ebtyf/cble/"  seamless="seamless" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" ></iframe></div>


**The Program Book can be downloaded [here](https://drive.google.com/file/d/1yRVp1cBqRnAbdYi4GXWV_pZeyWNsRquv/view?usp=sharing).**

#### **Letter from the President**

Welcome to the 2024 Meeting of the Cognitive Science Society in Rotterdam! CogSci 2024 brings together a large community of cognitive scientists who have traveled here from around the world, as well as a smaller group of remote presenters. I would like to extend an especially warm welcome to our first-time CogSci meeting attendees, and hope that 
their experience inspires them to join our future meetings for many years to come.

I want to thank this year’s conference co-chairs, Larissa K Samuelson, Stefan Frank, Mariya Toneva, Allyson Mackey, and Eliot Hazeltine, for putting together an amazing series of invited talks and symposia around the theme of Dynamics of Cognition. The co-chairs also deserve credit for handling a record-breaking number of submissions and producing a truly exciting conference program 

Beyond the invited talks and symposia dedicated to this year’s conference theme, I would like to highlight the presentations and events honoring the 
Rumelhart, Elman, Gleitman and C .L . de Carvalho Heineken prize winners, including the Rumelhart reception on Thursday. As you may know, we are recording all of the invited talks and symposia, and all prize-winners’ talks, and will be making this content available after the conference. 

The Cognitive Science Society relies on the volunteer efforts of our Governing Board members who work on matters related to our membership; conference policies; diversity and inclusion, international, and outreach initiatives; prizes and much more. We welcome interest from Society members who would like to become more involved in what we do. The 
Society is deeply grateful to Rick Dale and Andrea Bender, who serve as editors of the two Society journals, Cognitive Science and Topics in Cognitive Science respectively. We especially acknowledge our editors’ generosity in donating their stipends each year to D&I and outreach efforts. 

This year’s Annual Meeting depends critically on the support of Marischal De Armond and his team at Podium Conference Specialists: Sharon Zwack, Cendrine De Vis, Sarah-Kate Burke, and Rachel Waller worked tirelessly to secure the venue and handled a multitude of logistical and organizational issues, from arranging coffee breaks and receptions to making sure that a huge number of posters fits comfortably into the available space. Finally, and importantly, I would like to acknowledge the Cognitive Science Society Executive Officer, Erica Wojcik, for managing the complex and ever expanding sphere of our Society’s activities.

I hope you enjoy this year’s meeting and the many different opportunities to engage with the vibrant community of cognitive scientists gathered here. I also hope you get a chance to explore the great city of Rotterdam with its many attractions, museums, restaurants and scenic views. If you’d like to talk more about our Society, or simply want to say hello, please stop by!

![](https://assets.underline.io/markdown_image/1/image/3c66d0e21fff30e204df1138ffd15173.jpeg)

**Anna Papafragou**  
President, Cognitive Science 
Society 2023-2024

**CODE OF CONDUCT**<br>
By attending the CogSci 2024 Conference, you are required to adhere to the society’s [Code of Conduct](https://drive.google.com/file/d/16-6KkptF0Gn3ZYGJDlpqpwTdImw45Ng0/view?usp=drive_link).

**ABOUT THE COGNITIVE SCIENCE SOCIETY**<br>
The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education.

The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.
<br><br>

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To access the site please register [**here**](https://cognitivesciencesociety.org/registration/). 

The 46th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

Dependency length minimization is a universally observed quantitative property of natural languages. However, the extent of dependency length minimization, and the cognitive mechanisms through which the language processor achieves this minimization remain unclear. This research offers mechanistic insights by postulating that moving a short preverbal constituent next to the main verb explains preverbal constituent ordering decisions better than global minimization of dependency length in SOV languages. This approach constitutes a least-effort strategy because it’s just one operation but simultaneously reduces the length of all preverbal dependencies linked to the main verb. We corroborate this strategy using large-scale corpus evidence across all seven SOV languages that are prominently represented in the Universal Dependency Treebank. These findings align with the concept of bounded rationality, where decision-making is influenced by `quick-yet-economical' heuristics rather than exhaustive searches for optimal solutions. Overall, this work sheds light on the role of bounded rationality in linguistic decision-making and language evolution.

**Speakers:**

Sidharth Ranjan: University of Stuttgart; Titus von der Malsburg: University of Stuttgart

Work Smarter...Not Harder: Efficient Minimization of Dependency Length in SOV Languages

We examine the heterogeneity of text-based behavioral interventions in a series of 5 preregistered studies across one in-person and 10 online panels, with over 11000 respondents in total. We observe large heterogeneity across settings and paradigms. Model the heterogeneity we introduce a framework that measures typically omitted moderators: Fluid Intelligence, Attentiveness, Crystallized Intelligence, and Experience. Variation in these factors are associated with different effect sizes and explain variations across samples. Moderators are associated with effect sizes through two paths, with the intensity of the manipulation and with the effect of the manipulation directly. Our results motivate observing these moderators and provide a theoretical and empirical framework for understanding and predicting varying effect sizes in the social sciences.

**Speakers:**

Antonia Krefeld-Schwalb: Erasmus University Rotterdam; Prof. Eric J. Johnson: Columbia University; Eli Rosen Sugerman: Columbia University

Using Cognitive Variables to Explain Why Effect Sizes Differ in the Behavioral Sciences

Models based on the Transformer neural network architecture have seen success on a wide variety of tasks that appear to require complex ``cognitive branching''-- or the ability to maintain pursuit of one goal while accomplishing others. In cognitive neuroscience, success on such tasks is thought to rely on sophisticated frontostriatal mechanisms for selective gating, which enable role-addressable updating-- and later readout-- of information to and from distinct ``addresses'' of memory, in the form of clusters of neurons. However, Transformer models have no such mechanisms intentionally built-in. It is thus an open question how Transformers solve such tasks, and whether the mechanisms that emerge to help them to do so bear any resemblance to the gating mechanisms in the human brain. In this work, we analyze the mechanisms that emerge within a vanilla attention-only Transformer trained on a simple sequence modeling task inspired by a task explicitly designed to study working memory gating in computational cognitive neuroscience. We find that, as a result of training, the self-attention mechanism within the Transformer specializes in a way that mirrors the input and output gating mechanisms which were explicitly incorporated into earlier, more biologically-inspired architectures. These results suggest opportunities for future research on computational similarities between modern AI architectures and models of the human brain.

**Authors:**

Aaron Traylor: Brown University; Jack Merullo: Brown University; Michael J. Frank: Brown University; Ellie Pavlick: Brown University

Transformer Mechanisms Mimic Frontostriatal Gating Operations When Trained on Human Working Memory Tasks

This paper seeks to understand designers' abstraction in ill- structured problem-solving. We utilize a protocol study with expert designers to empirically analyze the abstraction process in the latent need problem setting. A logic-based abstraction schema is found to model the process the designers employed. The study reveals how designers utilize this schema, detailing, developing, and evaluating solutions for ill-structured problems. It highlights the recursive nature of abstraction and raises questions about the termination of the process in ill- structured domains. We conclude by proposing a computational model to further evaluate abstraction in complex problem-solving scenarios.

**Authors:** Ryan Bruggeman, Northeastern University; Chehade Ciliotta, Estefania
Northeastern University; Tucker J. Marion, Northeastern University; Paolo Ciuccarelli, Northeastern University  

Towards a Computational Model of Abstraction in Design Reasoning

This discussion group will be an open-ended conversation/question & answer
session about a new open access publication that has been in development
at The MIT Press for the past two and half years: the Open Encyclopedia of
Cognitive Science (OECS). We hope to solicit input from the cognitive science
community about topics they would like to see in the OECS. We are also hoping
to recruit authors who are interested in contributing to it. And, of course, we
will be happy to answer any questions that the cognitive science community
might have about this project.

Open Encyclopedia of Cognitive Science

What impacts what we remember about objects we have just encountered? Inﬂuential theories of learning suggest that more active engagement leads to stronger memories than passive observation. However, it is not clear which aspects of interaction lead to stronger memories, nor what kinds of memories are supported by active engagement. Here we conduct several experiments to investigate the impact of assembling an object on subsequent recognition and recall performance. We found that reconstructing a block tower by copying it part-by-part could impair subsequent memory for that tower, compared to passively viewing that tower. By contrast, when participants initially encoded each tower by building it from working memory, their subsequent recall was enhanced relative to when they held the tower in working memory without building it. Together our results suggest a complex relationship between the nature of our interactions with objects and our subsequent memories of them.0

How does assembling an object affect memory for it?

Understanding how infants acquire knowledge about real-world scenes and the kind of information they rely on is still unexplored. In this study, we aimed to investigate the relationship between action and scene information in infants. In a preferential looking paradigm, 18-month-olds were exposed to several trials in which they observed a human performing a given action and a subsequent simultaneous display of two scenes. One of the scenes was congruent with the action, representing the environment where the action is more likely to occur, whereas the other was incongruent. Results revealed a significant preference for looking at the congruent scene, accompanied by a longer first visit duration of that scene. Our findings show that the relation between action and scene information, previously reported for adults, is present already in infancy, suggesting a potential role of action information in shaping the acquisition of scene knowledge.

**Authors:**

Maja Blesic: Central European University; Agnes Kovacs: Central European University

Action Observation Influences Scene Perception in 18-Month-Olds

Models of genetic evolution are tested by counting alleles, and a good model successfully predicts which genes will be found where. Cultural evolution is changing humanity orders of magnitude faster than genetic evolution, but at present we lack a way to empirically ground models of cultural evolution in a quantitative, content-agnostic way analogous to counting alleles. Here we describe a new method for measuring the flow of memes through minds: an information-theoretic measure of culturally-transmitted information. We report initial empirical results using cloze completion tasks to measure the entropy of written English for a particular text across groups of Readers and Non-Readers. The difference in entropy (on the order of 0.1 bits per character) multiplied by the number of characters in the text is an expression of the amount of information from the text that has been retained by Readers, and which is therefore capable of influencing their behavior.

**Authors:**

Matthew Cashman: Harvard University; Damian E Blasi: Harvard University

Quantifying Culture: an Information-Theoretic Measure of how Memes Flow Through Minds

Cultural evolutionary theory has shown that social learning is adaptive across a broad range of conditions. However, humans frequently under-utilise beneficial social information in experimental settings – a phenomenon termed egocentric discounting. We tested the hypothesis that influence is affected by expected reliability using a two-player online task in which both participants answered the same questions in series. After a first attempt, player 2 saw either advice from player 1 or their actual answer (spying). We manipulated the payoff structure of the task such that it had either a cooperative, competitive, or asocial incentive. As predicted, advice was least honest and social information overall had the least influence in the competitive condition. Player 2 also chose to spy rather than receive advice when offered the choice. Unexpectedly and regardless of the payoff structure, advice was more influential when player 2 could choose information but spying was more influential otherwise.

**Authors:**

Robin Watson: Arizona State University; Thomas J. H. Morgan: Arizona State University

Can epistemic vigilance explain the underuse of social information? Evidence that a competitive incentive favoured dishonest advice and reduced the influence of social information.

We employ a drawing-based signaling game involving two AI models to explore factors that impact empirical regularities in the surface form of artificially evolved glyphs and their similarity to human visual signs. In our first experiment, we investigate the role of the models’ perception system on glyph line orientation and symmetry. We find that these characteristics are impacted by the input statistics of data used to pre-train models and, to a lesser extent, canvas shape and architectural model properties. Our second experiment analyzes the grapho-phonemic mapping that emerges when we integrate representations learned by a deep learning model trained for speech conversion into our setup.

**Authors:**

Alice Hein: Technical University of Munich; Klaus Diepold: Technical University Munich

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